The third reason for concern relates to the overall (i.e., worldwide or aggregate)
economic and ecological implications of climate change. Numerous studies have
addressed aggregate impacts, particularly in the context of integrated assessment.

19.5.1. Aggregate Analysis: An Assessment

Estimating the aggregate impact of climate change is an intricate task that
requires careful professional judgment and skills. Aggregate analysis is based
on the same tools as most distributional analysis and uses regional data as
inputs. Consequently, it shares with distributional analysis the methodological
difficulties and shortcomings discussed more fully in Section
19.4:

Choice of an appropriate (set of) numeraire(s) in which to express impacts

Need to overcome knowledge gaps and scientific uncertainties to provide
a comprehensive picture

Difficulties in modeling the effects of adaptation

Difficulties in forecasting baseline developments (such as economic and
population growth, technical progress).

In addition, analysts have to grapple with some issues that are generic to
aggregate analysis. The most important issue is spatial and temporal comparison
of impacts. Aggregating impacts requires an understanding of (or assumptions
about) the relative importance of impacts in different sectors, in different
regions, and at different times. Developing this understanding implicitly involves
value judgments. The task is simplified if impacts can be expressed in a common
metric, but even then aggregation is not possible without value judgments. The
value judgments that underlie regional aggregation are discussed and made explicit
in Azar and Sterner (1996), Fankhauser et al. (1997, 1998), and Azar (1999).
Aggregation across time and the issue of discounting are discussed in more detail
in TAR WGIIIChapter 7. Aggregate
impact estimates can be very sensitive to the aggregation method and the choice
of numeraire (see Chapter 1).

All of these factors make aggregate analysis difficult to carry out and reduce
our overall confidence in aggregate results. Nevertheless, aggregate studies
provide important and policy-relevant information.

19.5.2. Insights and Lessons: The Static Picture

Most impact studies assess the consequences of climate change at a particular
concentration level or a particular point in time, thereby providing a static
"snapshot" of an evolving, dynamic process. The SAR suggested that
the aggregate impact of 2xCO2expressed in monetary termsmight
be equivalent to 1.5-2.0% of world GDP. Estimated damages are slightly
lower (relative to GDP) in developed countries but significantly higher in developing
countriesparticularly in small island states and other highly vulnerable
countries, where impacts could be catastrophic (Pearce et al., 1996). The SAR
was careful, however, to point out the low quality of these numbers and the
many shortcomings of the underlying studies.

Since publication of the SAR, our understanding of aggregate impacts has improved,
but it remains limited. Some sectors and impacts have received more analytical
attention than others and as a result are better understood. Agricultural and
coastal impacts in particular are now well studied (see Boxes
19-2 and 19-3). Knowledge about the health
impacts of climate change also is growing (see Box
19-4). Several attempts have been made to identify other nonmarket impacts,
such as changes in aquatic and terrestrial ecological systems and ecosystem
services, but a clear and consistent quantification has not yet emerged.

Table 19-4 contains a summary of results from
aggregate studies that use money as their numeraire. The numerical results as
such remain speculative, but they can provide insights on signs, orders of magnitude,
and patterns of vulnerability. Results are difficult to compare because different
studies assume different climate scenarios, make different assumptions about
adaptation, use different regional disaggregation, and include different impacts.
The estimates by Nordhaus and Boyer (2000), for example, are more negative than
others because they factor in the possibility of catastrophic impact. The estimates
by Mendelsohn et al. (2000), on the other hand, are driven by optimistic assumptions
about adaptive capacity and baseline development trends, which result in mostly
beneficial impacts.

Standard deviations rarely are reported, but they are likely to be several
times larger than the "best guess." They are larger for developing countries,
where results generally are derived through extrapolation rather than direct
estimation. This is illustrated by the standard deviations estimated by Tol
(2001b), also reproduced in Table 19-4. These estimates
probably still underestimate the true uncertaintyfor example, because
they exclude omitted impacts and severe climate change scenarios. Note that
the aggregation can mask large standard deviations in estimates of damages to
individual sectors (Rothman, 2000).

An alternative indicator of climate change impact (excluding ecosystems) is
the number of people affected. Few studies directly calculate this figure, but
it is possible to compare the population of regions experiencing negative impacts
with that of positively affected regions. Such calculations suggest that a majority
of people may be negatively affected already at average global warming of 1-2°C.
This may be true even if the net aggregate monetary impact is positive because
developed economies, many of which could have positive impacts, contribute the
majority of global production but account for a smaller fraction of world population.
The quality of estimates of affected population is still poor, however. They
are essentially "back-of-the envelope" extensions of monetary models,
and the qualifications outlined in that context also apply here. In addition,
they do not consider the distribution of positive and negative effects within
countries.

On the whole, our confidence in the numerical results of aggregate studies
remains low. Nevertheless, a few generic patterns and trends are emerging in
which we have more confidence:

Market impacts are estimated to be lower than initially thought and in
some cases are estimated to be positive, at least in developed countries.
The downward adjustment is largely a result of the effect of adaptation, which
is more fully (although far from perfectly) captured in the latest estimates.
Efficient adaptation reduces the net costs of climate change because the cost
of such measures is lower than the concomitant reduction in impacts. However,
impact uncertainty and lack of capacity may make efficient and error-free
adaptation difficult.

Nonmarket impacts are likely to be pronounced, and many (but not all) of
the effects that have not yet been quantified could be negative. In particular,
there is concern about the impact on human health and mortality. Although
few studies have taken adequate account of adaptation, the literature suggests
substantial negative health impacts in developing countries, mainly because
of insufficient basic health care (e.g., Martens et al., 1997). There also
is concern about the impact on water resources (e.g., Arnell, 1999; Frederick
and Schwarz, 1999) and ecosystems (e.g., Markham, 1996; White et al., 1999).

"Horizontal" interlinkages such as the interplay between different
impact categories (e.g., water supply and agriculture), the effect of stress
factors that are not related to climate, adaptation, and exogenous development
trends are crucial determinants of impact but have not been fully considered
in many studies.

Estimates of global impact are sensitive to the way numbers are aggregated.
Because the most severe impacts are expected in developing countries, aggregate
impacts are more severe and thus more weight is assigned to developing countries.
Using a simple summing of impacts, some studies estimate small net positive
impacts at a few degrees of warming; others estimate small net negative impacts.
Net aggregate benefits do not preclude the possibility that a majority of
people will be negatively affectedsome of them severely so.

Overall, the current generation of aggregate estimates may understate the true
cost of climate change because they tend to ignore extreme weather events, underestimate
the compounding effect of multiple stresses, and ignore the costs of transition
and learning. However, studies also may have overlooked positive impacts of
climate change. Our current understanding of (future) adaptive capacity, particularly
in developing countries, is too limited, and the treatment of adaptation in
current studies is too varied, to allow a firm conclusion about the direction
of the estimation bias.